running.py

import logging
import sys
import os
import json
from utils import utils

from datetime import datetime 

logger = logging.getLogger('__main__')

def setup(args):
    """Prepare training session: read configuration from file (takes precedence), create directories.
    Input:
        args: arguments object from argparse
    Returns:
        config: configuration dictionary
    """

    config = args.__dict__  # configuration dictionary

    # Create output directory
    initial_timestamp = datetime.now()
    output_dir = config['output_dir']
    if not os.path.isdir(output_dir):
        raise IOError(
            "Root directory '{}', where the directory of the experiment will be created, must exist".format(output_dir))

    output_dir = os.path.join(output_dir, config['experiment_name'])

    formatted_timestamp = initial_timestamp.strftime("%Y-%m-%d_%H-%M-%S")
    config['initial_timestamp'] = formatted_timestamp
#    if (not config['no_timestamp']) or (len(config['experiment_name']) == 0):
#        rand_suffix = "".join(random.choices(string.ascii_letters + string.digits, k=3))
#        output_dir += "_" + formatted_timestamp + "_" + rand_suffix
    config['output_dir'] = output_dir
    config['save_dir'] = os.path.join(output_dir, 'checkpoints')
    config['model_dir'] = os.path.join(output_dir, 'complete_saved_model')    
    config['pred_dir'] = os.path.join(output_dir, 'predictions')
    #config['tensorboard_dir'] = os.path.join(output_dir, 'tb_summaries')
    utils.create_dirs([config['save_dir'], config['pred_dir']]) #, config['tensorboard_dir']

    # Save configuration as a (pretty) json file
    with open(os.path.join(output_dir, 'configuration.json'), 'w') as fp:
        json.dump(config, fp, indent=4, sort_keys=True)

    logger.info("Stored configuration file in '{}'".format(output_dir))

    return config